Closed ikahbasi closed 4 years ago
@imankahbasi I think solving this (e.g. making spike-test accurately pick up on things that will cause an issue with cross-correlation, and warning the user and optionally removing those data points) is really worthwhile, but I don't think this is the right way to do it for the reasons above - I'm going to close this PR.
I'm thinking about writing a C-function for spike-testing that effectively does the cross-correlation with one dummy template with all channels, and returns a mask to Python that can then be checked and issue locations properly reported. Unfortunately I don't have time to do this at the moment.
What does this PR do?
Spike test function is not make errors anymore. With removing the spiky data the process will continue on the rest of data.
Why was it initiated? Any relevant Issues?
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